Josep Amat

Positioning an underwater vehicle through image mosaicking

Mosaics have been commonly used as visual maps for undersea exploration and navigation. The position and orientation of an underwater vehicle can be calculated by integrating the apparent motion of the images which form the mosaic. A feature-based mosaicking method is proposed in this paper. The creation of the mosaic is accomplished in four stages: feature selection and matching, detection of points describing the dominant motion, homography computation and mosaic construction. In this work we demonstrate that the use of color and textures as discriminative properties of the image can improve, to a large extent, the accuracy of the constructed mosaic. The system is able to provide 3D metric information concerning the vehicle motion using the knowledge of the intrinsic parameters of the camera while integrating the measurements of an ultrasonic sensor. The experimental results of real images have been tested on the GARBI underwater vehicle.

Automatic guidance of an assistant robot in laparoscopic surgery

A robotic arm which automatically guides the camera in the laparoscopic surgery is presented. The goal of this work is to generate adequate camera control strategies to track the working scene during a surgical procedure. The system is based on the computer vision analysis of the laparoscopic image that allows the surgeon to identify the scenes relevant point from the surgical instruments.

Robust normalization of silhouettes for recognition applications

In this work we introduce a new silhouette normalization method, which is robust with respect to deformations and enables the use of image domain based similarity measures for recognition applications. It is shown that a template matching operation can provide an accurate shortlist of candidates suitable for a more exact matching engine in spite of projective transformations and silhouette deformations. This retrieval of similar shapes has a low computational cost and has been tested with silhouettes of natural and man-made objects.

Stereoscopic system for human body tracking in natural scenes

Human body detection and tracking in a scene constitutes a very active working field clue to their applicability to many areas, specially as a man-machine interface (MMI) means. The system presented aims to improve the reliability and efficiency of teleoperation. The system is of application to teleoperated manipulation in civil applications such as big robots in shipyards, mines, public works or even cranes. Image segmentation is performed from movement detection. The recognition of moving bodies is verified by means of a simplified articulated cylindrical model, thus allowing to operate with a low computational cost.

Human-Robot Interaction Based on a Sensitive Bumper Skin

In order to enable robots to work in close contact with humans or in environments with unknown obstacles, new reactive control strategies based on sensitive bumper skins are proposed. The aim of this work is to provide a robot with contact and force control based strategies that make it dependable, safe and with foreseeable behaviours. The sensory skin is composed of rigid-bumpers provided with deformation sensors incorporated in a flexible substrate. This solution is a compromise between a simple bumper skin and current array-based robot skins, with better potential performances but, more costly and with usability problems. Such sensitive bumpers cover all moveable links of the robot allowing the detection of collisions, measuring the force involved and locating the point of contact with reasonable precision and cost

Tracking capabilities in computer vision for industrial applications

A tracking system has been developed with a compromise between complexity and cost and efficiency in mind. The tracking system consists of a PC fitted with a specific one-card processor designed in our laboratory that acquires the image and implements the recognition algorithm at video rate. We describe the recognition method, the hardware architecture, and some applications and results. The system can be extended to track targets in 3-D using two cameras and two processors. Finally we describe different applications already tested: A robot servo-positioning system in moving parts operation, a tracking system for vehicles for traffic supervision and control, and a tracking system for people for the study of their behavior.

A tracking system for dynamic control of convoys

Abstract An experimental control system for the flexible transport of goods by convoys is described. In this transport system convoys can be built automatically. The goal is that every vehicle attach to or disengage from the convoy when it receives the corresponding order by remote control. Each trailer follows the previous one in the convoy by means of a specific vision module. The vision module consists of a low-cost hardware designed to acquire and binarize the image. The algorithms use this binary image to detect and locate a mark placed on the rear of the preceding trailer. From this information the guidance system defines the trajectory to be tracked and generates the control orders to the steering wheels. The trailers are automated guided vehicles (AGV), each having its own tracking system that does not require any physical contact.

Texture parametrization method for image segmentation

In this paper we define six parameters addressed to parametrize the texture characteristics of an image towards its segmentation. With the aim to operate at high speed, these parameters have been defined looking for an acceptable compromise between discrimination capacity and easyness to implement a specific architecture for them.

Motor-Model-Based Dynamic Scaling in Human–Computer Interfaces

This paper presents a study on how the application of scaling techniques to an interface affects its performance. A progressive scaling factor based on the position and velocity of the cursor and the targets improves the efficiency of an interface, thereby reducing the users workload. The study uses several human-motor models to interpret human intention and thus contribute to defining and adapting the scaling parameters to the execution of the task. Two techniques addressed to vary the control-display ratio are compared, and a new method for aiding in the task of steering is proposed.

Detection of small-size synthetic references in scenes acquired with a pixelated device

A synthetic reference (SR) or fiducial mark is a target that has been designed and placed within a scene in order to help to locate ob- jects. When a scene containing a small SR is acquired through a pix- elated device (such as a CCD camera) and this SR is located using a digitally computed normalized correlation search, there is a lowering of the correlation peak if the target SR is displaced a nonwhole number of pixels with respect to the position of the previously acquired model SR. We propose a framework where the lowering is related to detection reli- ability, in order to compare the performance of different sizes and shapes of SR. This framework has been applied to eight SRs having simple shapes, using synthetic scenes. Results show large differences in their detection reliability according to their shape. A SR in the shape of a 45-deg-tilted square shows the best behavior among all the studied shapes, and one can take advantage of this fact when designing an application dealing with small-size SRs.